MineEcho — security grade SAFE, quality 64/100

Security audit verdict: SAFE · quality 64/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by Health-Yang · Codex Skill · ★ 245

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is MineEcho safe to install? View the security audit →

About MineEcho

MineEcho A local-first Memory OS for personal AI assistants: remember, learn, use skills, and spend fewer tokens. 中文文档 MineEcho is a source-available, local-first AI assistant framework for building private, extensible assistant workflows on top of local services and user-owned knowledge. MineEcho is not meant to be just another chat UI. Its product loop is: Remember user preferences and past work. Learn from imported knowledge through Wiki++ and graph context. Use skills and external AI apps through one routing surface. Save context cost with TokenLess reducers and local metrics. Use MineEcho when a normal chat UI is too forgetful, a RAG app is too passive, and an agent framework is too noisy to run as a long-term personal assistant. Why MineEcho What Makes It Different Me

ai-agentai-assistantknowledge-graphlocal-firstmemoryopenclawpersonal-airagskillstypescript

Quick Facts

Stars245
Forks27
LanguageTypeScript
CategoryCodex Skill
Quality Score63.527372794713/100
Last Updated2026-06-05
Created2026-05-28
Platformsnode
Est. Tokens~1413k

Compatible Skills

These tools work well together with MineEcho for enhanced workflows:

  • swarmvault — semantic(0.31)+complementary+same_lang+similar_pop+shared_platform (61%)
  • Ori-Mnemos — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (59%)
  • vellum-assistant — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • claude-memory-mcp — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (57%)

MineEcho alternative? Top 6 similar tools

Looking for a MineEcho alternative? If you're comparing MineEcho with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • godmode by GodMode-Team · ⭐ 55

    Personal AI OS for Entrepreneurs. Ultimate OpenClaw setup in minutes. Experience frictionless flow states in y

  • omega-memory by omega-memory · ⭐ 218

    Persistent memory for AI coding agents

  • lucid-memory by JasonDocton · ⭐ 158

    Memory for AI that works like yours—local, instant, persistent. 13x faster than Pinecone, 5x leaner than RAG.

  • openclaw-desktop by rshodoskar-star · ⭐ 119

    🖥️ A native desktop client for OpenClaw premium UI experience without the browser. Built with Electron + Rea

  • gno by gmickel · ⭐ 109

    Local AI-powered document search and editing with first-in-class hybrid retrieval, LLM answers, WebUI, REST AP

  • openclaw-config by TechNickAI · ⭐ 75

    Give your AI assistant memory, skills, and autonomy. Persistent memory, integration skills, and autonomous wor

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Frequently Asked Questions

What is MineEcho?

MineEcho is Local-first Memory OS for personal AI assistants with L0-L3 memory, Wiki++ knowledge, skill routing, and TokenLess context compression.. It is categorized as a Codex Skill with 245 GitHub stars.

What programming language is MineEcho written in?

MineEcho is primarily written in TypeScript. It covers topics such as ai-agent, ai-assistant, knowledge-graph.

How do I install or use MineEcho?

You can find installation instructions and usage details in the MineEcho GitHub repository at github.com/Health-Yang/MineEcho. The project has 245 stars and 27 forks, indicating an active community.

What are the best alternatives to MineEcho?

The top alternatives to MineEcho on Agent Skills Hub include godmode, omega-memory, lucid-memory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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